Assignment 1b PH1820 Fall 2016 Due Tuesday September 6, 2016 at 11:59 pm.
These exercises use a dataset consisting of measurements of arsenic in well water and in the toenails of
people drinking it. The data were downloaded from StatLib, a collection of d

Assignment 6 PH1820 Fall 2016 Due by 11:59pm Tuesday October 18, 2016
Instructions: Please show all work. Write equations as requested by the book or the problem.
(Hypotheses, critical regions, estimated regression equation, matrix equations.) Upload the

Assignment 3 PH1820 Fall 2016 Due by 11:59pm Tuesday, September 20, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Ca

Assignment 4 PH1820 Fall 2016 Due by 11:59pm Tuesday, October 4, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Canva

Assignment 5 PH1820 Fall 2016 Due by 11:59pm Tuesday, October 11, 2016
Instructions: Please show all work. When using SAS for computations, please list\write the equations
you would use if you were doing it by hand. Upload the completed assignment to Canv

Assignment 2 PH1820 Fall 2016 Due by 11:59 pm Tuesday, September 13, 2016
29 points
Instructions: Please show all work and upload the completed assignment to Canvas. .pdf files are also
acceptable. You can find the dataset on Canvas, attached with this as

Assignment 7 PH1820 Fall 2016 Due by 11:59pm Tuesday, November 1, 2016
Instructions: Please show all work. Upload the completed assignment to Canvas. .pdf files are also
acceptable.
We recommend SAS as the computer package to use for the computations, but

Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
Linear model 1 (PH1915)
Hyunkyoung Kim (ID:2060071)
3. Conduct a simulation study to assess the sensitivity of the normal linear regression model to
ov